MSDH: matched subspace detector with heterogeneous noise

Yang, X. , Zhang, L., Gao, L. and Xue, J.-H. (2019) MSDH: matched subspace detector with heterogeneous noise. Pattern Recognition Letters, 125, pp. 701-707. (doi: 10.1016/j.patrec.2019.07.014)

Abstract

The matched subspace detector (MSD) is a classical subspace-based method for hyperspectral subpixel target detection. However, the model assumes that noise has the same variance over different bands, which is usually unrealistic in practice. In this letter, we relax the equal variance assumption and propose a matched subspace detector with heterogeneous noise (MSDH). In essence, the noise variances are different for different bands and they can be estimated by using iteratively reweighted least squares methods. Experiments on two benchmark real hyperspectral datasets demonstrate the superiority of MSDH over MSD for subpixel target detection.

• Item Type: Articles
• Additional Information: This work was partly supported by the Royal Society under Royal Society-Newton Mobility Grant IE161194, and by the National Natural Science Foundation of China under Grant 61711530239.
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Yang, Dr Xiaochen
• Authors: Yang, X., Zhang, L., Gao, L., and Xue, J.-H.
• College/School: College of Science and Engineering > School of Mathematics and Statistics > Statistics
• Journal Name: Pattern Recognition Letters
• Publisher: Elsevier
• ISSN: 0167-8655
• ISSN (Online): 1872-7344
• Published Online: 17 July 2019
• Copyright Holders: Copyright © 2019 Elsevier B.V.
• First Published: First published in Pattern Recognition Letters 125: 701-707
• Publisher Policy: Reproduced in accordance with the publisher copyright policy